1. Field of the Invention
The invention described herein is related to determining the responsiveness of the data transmission rate in a communication network to packet drops or packet marking. More specifically, the present invention actively drops or marks packets of data from an aggregate of flows in a communication network and then measures the data traffic rate subsequent thereto. In so doing, the present invention can detect an amount of traffic not conforming to the transmission protocol of the aggregate.
2. Description of the Prior Art
In recent years, much research has been conducted to identify and model non-conforming traffic in a communication network operating under the Transmission Control Protocol (TCP). Most of the research in this field models the network traffic as individual flows under steady state conditions. Recently, it has been determined that much of the traffic in a wide area network such as the Internet is composed of so-called mice traffic, which, on a per-flow basis, is short-lived and sparse. However, when measured across all flows, the mice traffic accounts for a large percentage of traffic on the Internet. Thus, measuring traffic on a per-flow basis may lead to inaccurate estimates thereof or may require highly complex models for making approximations.
In the Journal paper “Promoting the Use of End-to-End Congestion Control in the Internet”, (Floyd, S. and Fall, K.; IEEE/ACM Transactions on Networking, Vol. 7, No. 4, August 1999), the authors disclose a method of testing a TCP flow by comparing the steady state throughput thereof with a theoretical predicted value for conforming flows. If the test response is similar to the model output, the flow is considered to be TCP conforming. Thus, non-conforming flows may be identified and subsequently penalized in order to control congestion on the network. The disclosed method describes how large sustained individual flows may be tested for TCP conformance, however, as previously stated, the traffic on individual flows of the Internet consists of mice traffic, which is by no means a large sustained flow.
In the paper “The BLUE Active Queue Algorithms”, (Wu-Chang, F., et al.; IEEE/ACM Transactions on Networking, Vol. 10, No. 4, August 2002), the authors disclose a Stochastic Fair BLUE (SFB) queue management algorithm which can identify and rate-limit non-responsive flows using a small amount of state information of the network. SFB provides a per-flow responsiveness test by mapping different flows to parallel bins. Those bins that become overloaded are considered to be receiving a non-conforming flow. However, if many non-conforming flows in a traffic aggregate exist, it is likely that all bins will become overloaded and the SFB algorithm will not be able to distinguish between conforming and non-conforming flows.
Thus, in view of the shortcomings of the prior art, there exists an apparent need for a technique to quantify the responsiveness to packet drops of network traffic that may not be in a large, sustained flow.